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Data recorded for leaf size, and leaf vein and areole measurements taken from nine Magnoliaceae species

Citation

Shi, Peijian et al. (2022), Data recorded for leaf size, and leaf vein and areole measurements taken from nine Magnoliaceae species, Dryad, Dataset, https://doi.org/10.5061/dryad.8cz8w9gsv

Abstract

Across species, the density of major veins in leaves scales inversely with leaf area. Yet, minor vein density manifests no clear relationship with respect to leaf are, despite having the potential to provide important insights into the trade-off between investments in leaf mechanical support, hydraulics, and light interception. To examine this phenomenon, between 120−380 mature leaves from each of nine Magnoliaceae species were sampled from Nanjing Forestry University campus and Nanjing Botanical Garden, Chinese Academy of Sciences, Nanjing, China in 2019 and 2020. The leaves were boiled, and the epidermal and mesophyll tissues were removed. The remaining leaf skeleton was stained to obtain a clear leaf venation network. The software LEAF GUI was used to obtain the data of leaf size, leaf vein and areole traits. The large sample size data render it possible to explore the scaling relationships between leaf size and each trait of leaf veins and areoles. This data set includes the information of leaf length, leaf width, leaf area, total vein length, total vein area, mean areole area per leaf, and the number of the areole sizes per leaf of the nine Magnoliaceae species.

Methods

Leaf sampling

Leaves of nine species of Magnoliaceae (Magnolia amoena, Magnolia denudate, Magnolia soulangeana, Magnolia tomentosa, Michelia cavaleriei var. platypetala, Michelia chapensis, Michelia compressa, Michelia figo, and Michelia maudiae) were collected from Nanjing Botanical Garden, Chinese Academy of Sciences and Nanjing Forestry University Xinzhuang Campus, Nanjing, China. Fully expanded and fully developed leaves, at least three months old were sampled between July to September in 2019 and 2020. The sampling of leaves for any one species was completed well within one year, in order to avoid phenological changes in leaf architecture. However, the sampling of all the leaves from all of the species was not performed in the same year owing to the required heavy workload this would have necessitated. For each species, 300−500 leaves from three to five mature trees were randomly sampled from the middle canopy without distinguishing between sun leaves and shade leaves (because the objective was to explore general trends rather than focusing on the influence of light on the characteristics of leaf veins and areoles, which is nevertheless worthy of future research). Only non-damaged healthy leaves were sampled. Fresh leaves were wrapped in wet paper to minimize desiccation and brought to the laboratory within two hours after sampling.

Chemical treatment and image scanning of leaf veins

The leaves were labelled by attaching a small paper tag to their petioles. Each leaf was subsequently placed into a nylon mesh bag and boiled in a 5-10% NaOH solution for 30 minutes in an open stainless steel pot (ST24P1, Supor, Wuhan, China; diameter: 28 cm; capacity: 1.2 L). The boiled leaves were washed with running water, and a soft brush was used to carefully remove epidermal and mesophyll tissues. The remaining leaf skeleton was then stained by a 5% safranin solution. The chemically cleared leaves were scanned at 600 dpi using an Epson scanner (V550, Epson Indonesia, Batam, Indonesia; Figure 1 for representative examples of scanned chemically cleared leaves of the nine species). We initially sampled and boiled 300−500 leaves. The useable samples (with intact leaf veins) were between 120 and 380 leaves. By estimate, there was on average less than a 5% loss of leaf veins for each of the usable leaves. However, this loss is estimated to not substantially influence the results reported here because of the very large sample size for each the species examined in this study.

Acquisition of leaf vein and areole data

The software LEAF GUI developed using the Matlab platform (Price et al., 2011) was used to obtain leaf area, total leaf vein length, total leaf vein area, the number of areoles per leaf, and individual areole area from cleared leaf images. The total areole area was calculated by summing the areas of all individual areoles. Mean areole area was defined as the mean of all of the individual areole areas per leaf. The original RGB images were transformed into black and white binary images, and the adaptive threshold and global threshold were set in LEAF GUI to obtain ultra-clear leaf vein images. The thresholds were determined empirically for each leaf image. LEAF GUI does not provide midrib length. Thus, the R script developed by Shi et al. (2018) and Su et al. (2019) was used to obtain leaf length, which was defined as the distance from the leaf base to leaf apex regardless of lamina curvature, and leaf width, which was defined as the maximum distance between two orthogonal points of the leaf edge forming a straight line perpendicular to the leaf length axis. Leaf length was used as the substitute of midrib length, although for curved leaves, the numeric values of these traits can moderately differ. Given that most leaves had almost perfect bilateral symmetry, the difference between midrib and lamina lengths was judged to be negligible (Fig. 1).

The above contents were quoted from Shi et al. (2022).

References:

Price, C. A., O. Symonova, Y. Mileyko, T. Hilley, and J. S. Weitz. 2011. Leaf extraction and analysis framework graphical user interface: segmenting and analyzing the structure of leaf veins and areoles. Plant Physiology 155: 236–245.

Shi, P., Q. Miao, Ü. Niinemets, M. Liu, Y. Li, K. Yu, and K. J. Niklas. 2022. Scaling relationships of leaf vein and areole traits versus leaf size for nine Magnoliaceae species differing in venation density. American Journal of Botany in press.

Shi, P., D. A. Ratkowsky, Y. Li, L. F. Zhang, S. Y. Lin, and J. Gielis. 2018. A general leaf-area geometric formula exists for plants–evidence from the simplified Gielis equation. Forests 9: 714.

Su, J. L., K. J. Niklas, W. Huang, X. Yu, Y. Yang, and P. Shi. 2019. Lamina shape does not correlate with lamina surface area: an analysis based on the simplified Gielis equation. Global Ecology and Conservation 19: e00666.